Do not teach algorithms [computer science and mathematics teaching]

Author(s):  
M.A. Iqbal ◽  
S. Tahir
Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Chengmei Fan ◽  
M. Mobeen Munir ◽  
Zafar Hussain ◽  
Muhammad Athar ◽  
Jia-Bao Liu

Sierpinski networks are networks of fractal nature having several applications in computer science, music, chemistry, and mathematics. These networks are commonly used in chaos, fractals, recursive sequences, and complex systems. In this article, we compute various connectivity polynomials such as M -polynomial, Zagreb polynomials, and forgotten polynomial of generalized Sierpinski networks S k n and recover some well-known degree-based topological indices from these. We also compute the most general Zagreb index known as α , β -Zagreb index and several other general indices of similar nature for this network. Our results are the natural generalizations of already available results for particular classes of such type of networks.


2021 ◽  
Vol 30 (2) ◽  
pp. 9-21
Author(s):  
A. I. Chuchalin

It is proposed to adapt the new version of the internationally recognized standards for engineering education the Core CDIO Standards 3.0 to the programs of basic higher education in the field of technology, natural and applied sciences, as well as mathematics and computer science in the context of the evolution of STEM. The adaptation of the CDIO standards to STEM higher education creates incentives and contributes to the systematic training of specialists of different professions for coordinated teamwork in the development of high-tech products, as well as in the provision of comprehensive STEM services. Optional CDIO Standards are analyzed, which can be used selectively in STEM higher education. Adaptation of the CDIO-FCDI-FFCD triad to undergraduate, graduate and postgraduate studies in the field of science, technology, engineering and mathematics is considered as a mean for improving the system of three-cycle STEM higher education.


2020 ◽  
Author(s):  
Angelicque Tucker Blackmon ◽  

This report is an analysis of college chemistry, biology, computer science, and mathematics students' perceptions of STEM self-efficacy and study skills before and after an intervention.


Author(s):  
Anne Karabon ◽  
Neal Grandgenett ◽  
Michelle Friend ◽  
Amelia Lanier Knarr ◽  
Kota Takahashi

Author(s):  
Thiago Schumacher Barcelos ◽  
Ismar Frango Silveira

On the one hand, ensuring that students archive adequate levels of Mathematical knowledge by the time they finish basic education is a challenge for the educational systems in several countries. On the other hand, the pervasiveness of computer-based devices in everyday situations poses a fundamental question about Computer Science being part of those known as basic sciences. The development of Computer Science (CS) is historically related to Mathematics; however, CS is said to have singular reasoning mechanics for problem solving, whose applications go beyond the frontiers of Computing itself. These problem-solving skills have been defined as Computational Thinking skills. In this chapter, the possible relationships between Math and Computational Thinking skills are discussed in the perspective of national curriculum guidelines for Mathematics of Brazil, Chile, and United States. Three skills that can be jointly developed by both areas are identified in a literature review. Some challenges and implications for educational research and practice are also discussed.


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